Date of Award

9-2016

Document Type

Dissertation

Degree Name

Doctor of Psychology (PsyD)

Department

Graduate Department of Clinical Psychology

First Advisor

Rodger Bufford

Second Advisor

Kathleen Gathercoal

Third Advisor

Mark McMinn

Abstract

The Adult Attachment Interview (AAI) is perhaps the most widely used and best-known assessment tool for assessing adult attachment. Several methods for scoring and coding the AAI exist; the Dynamic Maturational Model of Attachment and Adaptation (DMM) offers one theoretical perspective that accounts for the dynamic nature of attachment in high-risk populations, and incorporates contemporary information processing theory (Crittenden, 2015a). Despite the AAI’s empirical and clinical power, its utilization in both clinical and research practice is time consuming and costly. Conversely, most self-report questionnaires are readily accessible, cost effective, and time efficient. Nevertheless, there has been concern regarding the psychometric properties of self-report attachment measures, as well as their divergence in theoretical basis from the AAI. The Dynamic Maturation Model Relationship Questionnaire (DMM-RQ) is a brief, categorical self-report measure that was created from the actual discourse of DMM-AAI transcripts; it offers a potential solution to these issues (Crittenden, 1998). The present study examined the relationship between participants’ DMM-AAI classifications and responses on the DMM-RQ in hopes of generating a more economical method of assessing adult attachment rooted in both the DMM and AAI tradition.

A group of 210 adults living in the U.K. completed both the DMM-AAI and the DMMRQ. Preliminary data analyses suggested that statements on the DMM-RQ are related to DMMAAI classifications, but not as originally thought (Pace, Crittenden, Bufford, & Smith, 2015). Thus new hypotheses regarding the relationship between the DMM-AAI and DMM-RQ were generated and tested using binomial logistic regression. Results found a significant relationship between statements on the DMM-RQ and DMM-AAI classifications, but the DMM-RQ showed little practical power in predicting DMM-AAI classifications. The current DMM-RQ did not provide assessment of adult attachment that is consistent with the DMM-AAI. It is proposed that the complex DMM-RQ statements be transformed into individual items rated on a seven-point continuum from strongly disagree to strongly agree. In this way, much more information about participant’s attachment styles could be gathered while allowing for independent observations and use of parametric statistics; perhaps the DMM-RQ’s predictive power could be enhanced.

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